What’s Next For Smart Beta?

It was about three hours into the excellent “Democratizing Quant” conference this spring where I lost my mind.

I don’t mean I was upset or anything. Far from it. The annual micro-conference co-hosted by Wes Grey of Alpha Architect and Villanova University was fantastic. Academics and practitioners from all over the globe presented some truly next-level thinking about how financial markets work. I was riveted the whole time.

No, I lost my mind as in, gray matter started running from my ears and I could no longer process human language effectively. Such was the depth of some of the math casually tossed up on the projector.

As investors, we live in a math-heavy world. Eavesdrop on any conversation between two of us, and you’ll hear discussions of basis points and duration and half the letters in the Greek alphabet.

This math is great. It’s what drew me to investing in the first place. I loved the idea that these seemingly straightforward concepts like “owning a company” or “buying a bond” were just doorways to a bottomless well of quantitative thinking. Heck, I still read academic papers on Sunday mornings just for the heck of it.

Regular Investors
But there’s a flip side to this. While some of us may like working our way through the numbers, most investors are just trying to get from point A to point B on their investment journey. They have jobs. They have families. They have hobbies; dare I say, they have lives.

As I sat there in my school chair at Villanova listening to fellow math nerds interrogate each other, it dawned on me that as awesome as it was, it was also part of the problem we face.

The rise of “smart beta” in the public consciousness is probably a good thing, in the sense that it’s helped educate a generation of investors and advisors on better ways to think about investment risk and patterns of return. Even if you never buy one, there’s real learning to be had in understanding how and why a min vol—or momentum, or quality or multifactor—ETF does what it does.

The challenge for ETF issuers is where to draw the line when baking the math into actual products. Most of us are pretty comfortable with the “style box” factors at this point. Decades of reading about small versus large, and growth versus value has gotten through. These are internalized.

Beyond Style/Size
But what about products that use options to put guardrails on portfolio returns? Or products that use long and short positions based on both growth and value metrics? Or products that use AI to monitor data streams for signals to switch up exposures?

All of these products exist. All of them do what they say they’re going to do on the label. And all of them are quite complex, and thus, can be difficult to explain.

When asked at the end of the Democratizing Quant conference what I thought about the event, my comment was simple: I love all the ideas and all the math. Now we just need a passel of English majors to come in and figure out how to explain it. Communication—that’s the true next-frontier for smart beta ETFs.